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dbcsp  

Distance-Based Common Spatial Patterns
View on CRAN: Click here


Download and install dbcsp package within the R console
Install from CRAN:
install.packages("dbcsp")

Install from Github:
library("remotes")
install_github("cran/dbcsp")

Install by package version:
library("remotes")
install_version("dbcsp", "0.0.2.1")



Attach the package and use:
library("dbcsp")
Maintained by
Itsaso Rodríguez-Moreno
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-07-09
Latest Update: 2022-06-30
Description:
A way to apply Distance-Based Common Spatial Patterns (DB-CSP) techniques in different fields, both classical Common Spatial Patterns (CSP) as well as DB-CSP. The method is composed of two phases: applying the DB-CSP algorithm and performing a classification. The main idea behind the CSP is to use a linear transform to project data into low-dimensional subspace with a projection matrix, in such a way that each row consists of weights for signals. This transformation maximizes the variance of two-class signal matrices.The dbcsp object is created to compute the projection vectors. For exploratory and descriptive purpose, plot and boxplot functions can be used. Functions train, predict and selectQ are implemented for the classification step.
How to cite:
Itsaso Rodríguez-Moreno (2021). dbcsp: Distance-Based Common Spatial Patterns. R package version 0.0.2.1, https://cran.r-project.org/web/packages/dbcsp
Previous versions and publish date:
0.0.1.0 (2021-07-09 10:40), 0.0.2.0 (2022-02-17 17:32)
Other packages that cited dbcsp R package
View dbcsp citation profile
Other R packages that dbcsp depends, imports, suggests or enhances
Functions, R codes and Examples using the dbcsp R package
Some associated functions: AR.data . boxplot.dbcsp . dbcsp-class . dbcsp-package . plot.dbcsp . predict.dbcsp . print.dbcsp . selectQ . summary.dbcsp . train.dbcsp . 
Some associated R codes: CSP.R . auxiliar_functions.R . compB.R . data.R . dbcsp-package.R . dbcsp.R .  Full dbcsp package functions and examples
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